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Updated: Jun 30, 2026
The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Brain age gap in multiple sclerosis: associated with disability but independent of serum biomarkers
Marc Pawlitzki1,2, Patricia Kirschner2, Lars Masanneck2,3
1Department of Neurology, Heinrich-Heine University Duesseldorf, Moorenstraße 5, Duesseldorf 40225, Germany.
Background:
Multiple sclerosis (MS) is influenced by age-related brain alterations and affects cellular aging mechanisms. Machine-learning models can estimate brain-predicted age from magnetic resonance imaging (MRI) to quantify these aging-related changes.
Objectives:
This study examines whether the difference between predicted and chronological age (BrainAGE) relates to clinical disability and biomarkers of neuro-axonal injury in MS.
Design:
This study analyzed brain-predicted age from structural 3D T1-weighted MRI in 82 patients with relapsing MS enrolled in three prospective clinical trials and 30 healthy controls.
Methods:
BrainAGE, calculated as MRI-predicted minus chronological age, was correlated with the Expanded Disability Status Scale (EDSS), MS Functional Composite subtests, and serum neurofilament light chain and glial fibrillary acidic protein.
Results:
The mean chronological age of patients and healthy controls included in this study was 39.2 and 40.9 years, respectively. Patients with MS (n = 82) showed a higher BrainAGE (6.48 ± 6.83 years) than controls (n = 30; 0.69 ± 6.5 years; p = 0.0002). BrainAGE increased stepwise from controls to patients with EDSS < 3 and EDSS ⩾3 (p < 0.0001). Higher BrainAGE correlated with worse 9-Hole Peg Test (9HPT, ρ = 0.34, p = 0.002) and Timed 25-Foot Walk performance (T25FW, ρ = 0.23, p = 0.043), but not with serum neurofilament light chain (p = 0.68) or glial fibrillary acidic protein (p = 0.33). In multivariable regression models adjusting for chronological age, sex, disease duration, and disease-modifying therapy, BrainAGE remained significantly associated with EDSS, 9HPT, and T25FW performance. sNfL and sGFAP remained nonsignificant after adjustment.
Conclusion:
Our findings suggest that BrainAGE and serum biomarkers capture complementary aspects of MS pathology, supporting a multimodal approach to assess disease progression.
Trial Registration:
ClinicalTrials.gov ID: SATURATE: NCT05701423, 360PMS: NCT06501950, SAFEGUIDE-MS: NCT06461481.
